The Unassuming Economist

From a paper by Boqiang Lin, and Yijie Song:

“Macroeconomic factors such as coal prices affect corporate decision making. With a set of 39,795 observations of firm-year data, encompassing 30 provinces and spanning the years 2005–2022, this paper estimates the impact of coal price shocks to corporate risk-taking of listed companies in China. The empirical results show that coal prices change negatively affect corporate risk-taking due to internal risk aversion. Further analysis shows that this effect is asymmetric between positive and negative shocks, and is more significant among higher coal dependence provinces. External factors such as economic policy uncertainty further reduce risk-taking. This study provides both macro and micro perspective analysis of corporate risk-taking and coal prices influences, contributing to the policy references for corporate strategic choices and coal price adjustments in the process of energy transition of China.”

From a paper by Khoirina Cahyani Rahmawati & Widita Kurniasari:

“This study aims to determine the implementation of Okun’s Law, namely the effect of economic growth on the unemployment rate in 30 countries on the Asian continent in the period 2016-2022. The independent variable in this study is economic growth while the dependent variable is the unemployment rate and in this study has control variables namely foreign direct investment, inflation and trade openness. This research uses secondary data obtained from the World Bank. The analysis method in this study uses the panel data regression analysis method on 30 countries on the Asian continent in 2016-2022 using the Stata application. The best model at this stage of the research is the Random Effect Model (REM). Based on the results of the research conducted, it can be seen that (1) the economic growth variable shows a negative and significant relationship with the unemployment rate, (2) the foreign direct investment variable shows a negative relationship and has no significant effect on the unemployment rate, (3) the inflation variable shows a positive and significant relationship with the unemployment rate, (4) the trade openness variable shows a negative and significant relationship with the unemployment rate.”

From Devdiscourse:

“The Confederation of Indian Industry (CII) has urged for employment-centered initiatives in the upcoming FY26 budget to enhance job creation and foster inclusive growth across India. Notably, the CII has proposed a comprehensive seven-point strategy to harness India’s demographic potential effectively.

Among the key recommendations, CII suggests establishing an integrated national employment policy and bolstering labour-intensive sectors. It proposes creating new short-term employment through government internships for the youth in rural areas to bridge the gap between education and job skills. It also emphasizes boosting female workforce participation through dormitory construction and the formalization of sectors like the care economy.

Moreover, there’s a call for an international mobility authority under the Ministry of External Affairs to help young Indians access overseas employment opportunities. This authority aims to collaborate on skill development aligned with global prospects, including language and cultural preparation. CII underscores the need for enhanced productivity alongside job growth, urging for strategic measures to lower India’s Incremental Capital Output Ratio (ICOR).”

From a paper by Prince Mensah Osei, Johnny Lo, Ute Mueller, Steven Richardson, and Ebenezer Afrifa-Yamoah:

“Time-frequency domain analysis of housing prices can provide insights into significant periodic patterns in the pricing dynamics for modelling and forecasting purposes. This study applied wavelet and information entropy analyses to examine the periodic patterns and evolution of housing prices in Australia’s eight capital cities from 1980 to 2023, using quarterly median house pricing data. Our findings revealed consistent patterns of higher variability in housing prices at high frequencies across all cities, with Melbourne exhibiting the highest variability. This indicates that short-term price fluctuations were higher than long-term changes. Perth and Brisbane demonstrated notable cyclical patterns with recurring periods of growth and decline. Coherence analyses revealed dynamic lead–lag relationships, both positive and negative, between housing prices of various cities, suggesting interconnectedness but not always synchronisation. Some cities’ housing prices dominated the information sharing, indicating varying degrees of influence within the national market. These findings highlight the complex, dynamic interdependencies among Australia’s major city housing markets, providing valuable insights for policymakers, investors, and stakeholders in economic forecasting, policy development and strategic planning within these markets.”

From a paper by Khoja Akhmet Yassawi, Mukhtar Auezov, and Miras University:

“The investigation delved into the dynamic interplay between oil price fluctuations and their ramifications on the pricing of agricultural products, employing the Vector Autoregression methodology. The dataset spanned 3 months, commencing from January 2010 and concluding in December Upon subjecting the data to an in-depth analysis, it was ascertained that it possesses a unit root, indicating an integrated order of one (I [1]), and achieves stationarity subsequent to the first-order differencing. The findings of the inquiry revealed that the paramount driver influencing agricultural product prices is the inherent volatility within the agricultural sector itself. Contrary to initial expectations, the impact of oil price fluctuations on agricultural prices was discerned to be comparatively modest. Intriguingly, the outcomes underscored that the preeminent factor contributing to fluctuations in agricultural product prices is the influence wielded by oil prices. This implies that alterations in oil prices exert a more pronounced effect on the variability in agricultural product prices as opposed to the overall revenue generated from agricultural endeavors.”